Performance Analysis of Optimization Based FOC and DTC Methods for Three Phase Induction Motor

Three-phase induction motors are becoming increasingly utilized in industrialfield due to their better efficiency and simple manufacture.The speed control of an induction motor is essential in a variety of applications,but it is dif-ficult to control.This research analyses the three-phase induction motor’s perfor-mance usingfield-oriented control(FOC)and direct torque control(DTC)techniques.The major aim of this work is to provide a critical evaluation of devel-oping a simple speed controller for induction motors with improving the perfor-mance of Induction Motor(IM).For controlling a motor,different optimization approaches are accessible;in this research,a Fuzzy Logic Controller(FLC)with Fractional Order Darwinian Particle Swarm Optimization(FODPSO)algorithm is presented to control the induction motor.The FOC and DTC are controlled using FODPSO,and their performance is compared to the traditional FOC and DTC technique.Each scheme had its own simulation model,and the results were com-pared using hardware experimental and MATLAB-Simulink.In terms of time domain specifications and torque improvement,the proposed technique surpasses the existing method.

SAR target detection based on the optimal fractional Gabor spectrum feature

In this paper,an algorithm based on a fractional time-frequency spectrum feature is proposed to improve the accuracy of synthetic aperture radar(SAR)target detection.By extending the fractional Gabor transform(FrGT)into two dimensions,the fractional time-frequency spectrum feature of an image can be obtained.In the achievement process,we search for the optimal order and design the optimal window function to accomplish the two-dimensional optimal FrGT.Finally,the energy attenuation gradient(EAG)feature of the optimal time-frequency spectrum is extracted for high-frequency detection.The simulation results show the proposed algorithm has a good performance in SAR target detection and lays the foundation for recognition.

A NEW NONCONFORMING MIXED FINITE ELEMENT SCHEME FOR THE STATIONARY NAVIER-STOKES EQUATIONS

In this article, a new stable nonconforming mixed finite element scheme is proposed for the stationary Navier-Stokes equations, in which a new low order Crouzeix- Raviart type nonconforming rectangular element is taken for approximating space for the velocity and the piecewise constant element for the pressure. The optimal order error estimates for the approximation of both the velocity and the pressure in L2-norm are established, as well as one in broken H1-norm for the velocity. Numerical experiments are given which are consistent with our theoretical analysis.

Self-adaptive strategy for one-dimensional finite element method based on EEP method with optimal super-convergence order

Based on the newly-developed element energy projection （EEP） method with optimal super-convergence order for computation of super-convergent results, an improved self-adaptive strategy for one-dimensional finite element method （FEM） is proposed. In the strategy, a posteriori errors are estimated by comparing FEM solutions to EEP super-convergent solutions with optimal order of super-convergence, meshes are refined by using the error-averaging method. Quasi-FEM solutions are used to replace the true FEM solutions in the adaptive process. This strategy has been found to be simple, clear, efficient and reliable. For most problems, only one adaptive step is needed to produce the required FEM solutions which pointwise satisfy the user specified error tolerances in the max-norm. Taking the elliptical ordinary differential equation of the second order as the model problem, this paper describes the fundamental idea, implementation strategy and computational algorithm and representative numerical examples are given to show the effectiveness and reliability of the proposed approach.

Probability distribution of wind power volatility based on the moving average method and improved nonparametric kernel density estimation

In the process of large-scale,grid-connected wind power operations,it is important to establish an accurate probability distribution model for wind farm fluctuations.In this study,a wind power fluctuation modeling method is proposed based on the method of moving average and adaptive nonparametric kernel density estimation(NPKDE)method.Firstly,the method of moving average is used to reduce the fluctuation of the sampling wind power component,and the probability characteristics of the modeling are then determined based on the NPKDE.Secondly,the model is improved adaptively,and is then solved by using constraint-order optimization.The simulation results show that this method has a better accuracy and applicability compared with the modeling method based on traditional parameter estimation,and solves the local adaptation problem of traditional NPKDE.

CHARACTERISTIC FINITE DIFFERENCE ALTERNATING-DIRECTION METHOD ANDANALYSIS FOR NUMERICAL RESERVOIR SIMULATION

Petroleum science has made remarkable progress in organic geochemistry and in the research into the theories of petroleum origin, its transport and accumulation. In estimating the oil-gas resources of a basin, the knowledge of its evolutionary history and especially the numerical computation of fluid flow and the history of its changes under heat is vital. The mathematical model call be described as a coupled system of nonlinear partial differentical equations with initial-boundary value problems. This thesis, from actual conditions such as the effect of fluid compressibility and the characteristic of large-scal science-engineering computalion. puts forward a kind of characteristic finite difference alternating-direction scheme. Optimal order estimates in L-2 norm are derived for the error in the approximate solutions.

THEORY AND APPLICATION OF FRACTIONAL STEP CHARACTERISTIC FINITE DIFFERENCE METHOD IN NUMERICAL SIMULATION OF SECOND ORDER ENHANCED OIL PRODUCTION

A kind of second-order implicit fractional step characteristic finite difference method is presented in this paper for the numerically simulation coupled system of enhanced （chemical） oil production in porous media. Some techniques, such as the calculus of variations, energy analysis method, commutativity of the products of difference operators, decomposition of high-order difference operators and the theory of a priori estimates are introduced and an optimal order error estimates in l^2 norm is derived. This method has been applied successfully to the numerical simulation of enhanced oil production in actual oilfields, and the simulation results ate quite interesting and satisfactory.

Modified characteristic finite difference fractional step method for moving boundary value problem of nonlinear percolation system

A fractional step scheme with modified characteristic finite differences run- ning in a parallel arithmetic is presented to simulate a nonlinear percolation system of multilayer dynamics of fluids in a porous medium with moving boundary values. With the help of theoretical techniques including the change of regions, piecewise threefold quadratic interpolation, calculus of variations, multiplicative commutation rule of differ- ence operators, multiplicative commutation rule of difference operators, decomposition of high order difference operators, induction hypothesis, and prior estimates, an optimal order in 12 norm is displayed to complete the convergence analysis of the numerical algo- rithm. Some numerical results arising in the actual simulation of migration-accumulation of oil resources by this method are listed in the last section.

Local Discontinuous Galerkin Methods with Novel Basis for Fractional Diffusion Equations with Non-smooth Solutions

In this paper,we develop novel local discontinuous Galerkin(LDG)methods for fractional diffusion equations with non-smooth solutions.We consider such problems,for which the solutions are not smooth at boundary,and therefore the traditional LDG methods with piecewise polynomial solutions suffer accuracy degeneracy.The novel LDG methods utilize a solution information enriched basis,simulate the problem on a paired special mesh,and achieve optimal order of accuracy.We analyze the L2 stability and optimal error estimate in L2-norm.Finally,numerical examples are presented for validating the theoretical conclusions.

Theory and application of numerical simulation method of capillary force enhanced oil production

A kind of second-order implicit upwind fractional step finite difference methods are presented for the numerical simulation of coupled systems for enhanced （chemical） oil production with capillary force in the porous media. Some techniques, e.g., the calculus of variations, the energy analysis method, the commutativity of the products of difference operators, the decomposition of high-order difference operators, and the theory of a priori estimate, are introduced. An optimal order error estimate in the l2 norm is derived. The method is successfully used in the numerical simulation of the enhanced oil production in actual oilfields. The simulation results are satisfactory and interesting.

MIXED DISCONTINUOUS GALERKIN METHOD FOR QUASI-NEWTONIAN STOKES FLOWS

In this paper,we introduce and analyze an augmented mixed discontinuous Galerkin(MDG)method for a class of quasi-Newtonian Stokes flows.In the mixed formulation,the unknowns are strain rate,stress and velocity,which are approximated by a discontinuous piecewise polynomial triplet ■for k≥0.Here,the discontinuous piecewise polynomial function spaces for the field of strain rate and the stress field are designed to be symmetric.In addition,the pressure is easily recovered through simple postprocessing.For the benefit of the analysis,we enrich the MDG scheme with the constitutive equation relating the stress and the strain rate,so that the well-posedness of the augmented formulation is obtained by a nonlinear functional analysis.For k≥0,we get the optimal convergence order for the stress in broken ■(div)-norm and velocity in L^(2)-norm.Furthermore,the error estimates of the strain rate and the stress in-norm,and the pressure in L^(2)-norm are optimal under certain conditions.Finally,several numerical examples are given to show the performance of the augmented MDG method and verify the theoretical results.Numerical evidence is provided to show that the orders of convergence are sharp.

On First Order Optimality Conditions for Vector Optimization

We develop first order optimality conditions for constrained vector optimization. The partial orders for the objective and the constraints are induced by closed and convex cones with nonempty interior. After presenting some well known existence results for these problems, based on a scalarization approach, we establish necessity of the optimality conditions under a Slater-like constraint qualification, and then sufficiency for the K-convex case. We present two alternative sets of optimality conditions, with the same properties in connection with necessity and sufficiency, but which are different with respect to the dimension of the spaces to which the dual multipliers belong. We introduce a duality scheme, with a point-to-set dual objective, for which strong duality holds. Some examples and open problems for future research are also presented.

Fractional Order Darwinian Pigeon-Inspired Optimization for Multi-UAV Swarm Controller

This paper presents a novel multiple unmanned aerial vehicde(UAV)swarm cotoller based on the fractional alculus theory.This controller i designed baed on fractional order Darwinian pigeon-inepired optimization(F 0DPI0)and PID algorithm.Several comparative simulations are conducted in the paper.The simulation results reveal that FODPIObased muli-UAV formation controller is superior to the basic PIO and dilTerential evolution(DE)method.The fractional oelfcdent in F ODPIO algorithm makes it eflective optimbation with fast convergence rate,small oversboot,and better stability.Therefore,the contnoller propoeed in this paper is fessible and robust.

A LOW ORDER NONCONFORMING MIXED FINITE ELEMENT METHOD FOR NON-STATIONARY INCOMPRESSIBLE MAGNETOHYDRODYNAMICS SYSTEM

A low order nonconforming mixed finite element method(FEM)is established for the fully coupled non-stationary incompressible magnetohydrodynamics(MHD)problem in a bounded domain in 3D.The lowest order finite elements on tetrahedra or hexahedra are chosen to approximate the pressure,the velocity field and the magnetic field,in which the hydrodynamic unknowns are approximated by inf-sup stable finite element pairs and the magnetic field by H^(1)(Ω)-conforming finite elements,respectively.The existence and uniqueness of the approximate solutions are shown.Optimal order error estimates of L^(2)(H^(1))-norm for the velocity field,L^(2)(L^(2))-norm for the pressure and the broken L^(2)(H^(1))-norm for the magnetic field are derived.

ANISOTROPIC CROUZEIX-RAVIART TYPE NONCONFORMING FINITE ELEMENT METHODS TO VARIATIONAL INEQUALITY PROBLEM WITH DISPLACEMENT OBSTACLE

In this paper, anisotropic Crouzeix-Raviart type nonconforming finite element meth- ods are considered for solving the second order variational inequality with displacement obstacle. The convergence analysis is presented and the optimal order error estimates are obtained under the hypothesis of the finite length of the free boundary. Numerical results are provided to illustrate the correctness of theoretical analysis.

A NOTE ON THE QUADRILATERAL MESH CONDITION RDP(N,ψ)

The main aim of this paper is to show that the quadrilateral mesh condition RDP（N, ψ） is only sufficient but not necessary for the optimal order error estimate of the Q isoparametric element in the Hi norm.

Centralized Decisions for a Two-Stage Supply Chain with Price-Discount Dependent Demand

In this paper,we study a centralized supply chain for a two-stage with selling price discount.This supply chain consists of a supplier and a retailer. Based on the feature that the product’s selling season is short and the supply chain faces great demand uncertainty. We consider a two-stage scenario where,at the beginning of stage 1,the supplier reserves production capacity based on historic data in advance,stage 2 comes to us after some leadtime,both the supplier and the retailer update the demand information,the retailer then places an order not exceeding the reserved capacity based on the selling-pricing discount dependent demand. We make optimal decisions on the reserved capacity in stage 1,selling price discount and order quantity in stage 2. In this supply chain,the pattern in stage2 is figured out first,and then stage 1 is cleared as well. Then we present a numerical example to give some insights. Finally we get some conclusions.

A Mixed Regularization Method for Ill-Posed Problems

In this paper we propose a mixed regularization method for ill-posed prob-lems.This method combines iterative regularization methods and continuous regular-ization methods effectively.First it applies iterative regularization methods in which there is no continuous regularization parameter to solve the normal equation of the ill-posed problem.Then continuous regularization methods are applied to solve its residual problem.The presented mixed regularization algorithm is a general framework.Any iterative regularization method and continuous regularization method can be combined together to construct a mixed regularization method.Our theoretical analysis shows that the new mixed regularization method is with optimal order of error estimation and can reach the optimal order under a much wider range of the regularization parameter than the continuous regularization method such as Tikhobov regularization.Moreover,the new mixed regularization method can reduce the sensitivity of the regularization parameter and improve the solution of continuous regularization methods or iterative regularization methods.This advantage is helpful when the optimal regularization pa-rameter is hard to choose.The numerical computations illustrate the effectiveness of our new mixed regularization method.

Monitoring and Limiting Deceptive Counterfeiting:a Two-Stage Model

Over past decades,deceptive counterfeits which cannot be recognized by ordinary consumers when purchasing,such as counterfeit cosmetics,have posed serious threats on consumers’health and safety,and resulted in huge economic loss and inestimable brand damages to the genuine goods at the same time.Thus,how to effectively control and eliminate deceptive counterfeits in the market has become a critical problem to the local government.One of the principal challenges in combating the cheating action for the government is how to enhance the enforcement of relative quality inspection agencies like industrial administration office(IAO).In this paper,we formulate a two-stage counterfeit product model with a fixed checking rate from IAO and a penalty for holding counterfeits.Tominimize the total expected cost over two stages,the retailer adopts optimal ordering policies which are correlated with the checking rate and penalty.Under certain circumstances,we find that the optimal expected cost function for the retailer is first-order continuous and convex.The optimal ordering policy in stage two depends closely on the inventory level after the first sales period.When the checking rate in stage one falls into a certain range,the optimal ordering policy for the retailer at each stage is to order both kinds of products.Knowing the retailer’s optimal ordering policy at each stage,IAO can modify the checking rate accordingly to keep the ratio of deceptive counterfeits on the market under a certain level.